We’ve been hearing for years that digital marketing is changing fast. We’ve become accustomed to running behind the latest Google algorithm, the newest TikTok feature or the latest AI-enabled tool. But what’s coming towards the 2030 horizon isn’t just a tool upgrade, it ‘s a global operating system change.
If we take a cold look at the macroeconomic and technological environment, the transformation we are facing is not an evolution, it is an adaptive response to an environment that is fundamentally hostile to traditional business models.
Let’s not kid ourselves: the game has changed because the economic rules have been broken. And most of the industry is still looking at the finger instead of the moon.
The technology deflation trap
To understand where we are going, you first have to look at the portfolio. The underlying phenomenon that is reshaping market strategies is not AI, it is technologydeflation1 .
We live in a cruel paradox: technology multiplies efficiency and makes production cheaper, but this destroys nominal value. The smartphone phagocytosed the camera, the GPS, the encyclopedia and the tape recorder, reducing the overall turnover of all these industries and destroying accounting “wealth” in the process.
In this scenario of automated abundance, the monetary value of purely functional solutions tends to zero. If your marketing strategy is based on functional features (“the SW that reduces your process time by 40%”), you are dead, because those features are easily replicable and subject to brutal downward price pressure.
Marketing ceases to be a cost center and becomes the only survival mechanism: either you build monopolistic differentiation based on intangibles and neurological experiences, or you sink into perfect low-price competition6.
But here comes the real plot twist: who do you have to convince of that value?
Welcome to the B2A era: Business-to-Agent
The most disruptive trend for the second half of this decade is the transition from generative AI (which creates text or images) to agentic AI (which executes actions).
This is the birth of the Business-to-Agent (B2A) model. Forget traditional B2C and B2B. In a very short time, your main customer will no longer be a human being but an autonomous software agent acting on your behalf.
Think about it for a second. We will move from LLMs (Language Models) to LAMs (Action Models). An agent won’t just suggest a flight; they’ll go online, select the seat and pay with your card without you lifting a finger.
This destroys the sales funnel as we know it. The model becomes B2B2A (Business-to-Business-to-Agent). The agent acts like a ruthless bouncer. If a user asks your agent to “buy eco-friendly detergent at the best value for money,” the algorithm will evaluate thousands of options in milliseconds based on data, completely ignoring your precious emotional banner or your visual brand positioning.
Persuasion changes sides: it is no longer about capturing the human’s visual attention, but about convincing the algorithm that your choice is the mathematically optimal one.
M2M Marketing: Speak the language of machines
To survive in this agentic commerce, brands need a total reengineering of their information. We need Machine-to-Machine Marketing (M2M) strategies.
What does this mean in practice?
- Agent-Ready Catalogs: Your product information cannot be sequestered in a PDF or vague marketing copy. It must be exposed through APIs with rich, standardized metadata that an agent can objectively compare.
- Radical transparency: Agents will penalize uncertainty. You need APIs that expose stock and guaranteed delivery times in real time. If the agent can’t verify that you have the product, he won’t buy from you.
- Logical offers: Goodbye to the visual “2 for 1” coupon. Offers should be logical rules that are calculable and verifiable by the machine at the time of the transaction.
From SEO to GEO: The battle for entities
If agents buy, how do they search? Traditional “ten blue links” search engines are being replaced by generative response engines. This forces us to evolve from SEO to GEO (Generative Engine Optimization).
AI models do not think in “keywords”, they think in Entities and semantic relationships. Your brand must establish itself as an authoritative entity in the knowledge graph. It is no longer about positioning for a keyword, but about building a digital footprint that associates your brand with the desired attributes across the web.
And for this, the Schema Markup becomes critical. We must implement deep schemas (Product, Organization, HowTo) for AI to unambiguously extract price, availability and valuations. In fact, we will see the emergence of AI agents dedicated exclusively to autonomous schema optimization, which will repair and generate structured data in real time.
The Invisible Infrastructure: The USB-C of AI
This all sounds great, but it requires plumbing. Data fragmentation has always been our Achilles heel. The coming solution is Model Context Protocol (MCP), the open standard that promises to be the “USB-C port” for AI applications.
MCP allows an AI (such as Claude or ChatGPT) to connect to your internal databases or management tools without costly ad-hoc integrations23. This will enable seamless agentic orchestration: artificial intelligences querying your sales data in real time, cross-referencing it with weather and adjusting your Google Ads campaigns automatically without human intervention.
Preparing the brand for the MCP ecosystem will be as important a technical priority as having a responsive website was back in the day.
Polarization: Logic for the machine, Magic for the human.
So where is the human being in all this?
Herein lies the key to future strategy: duality. Brands will have to operate simultaneously in two realities: the algorithmic and the sensory.
While agents take care of the logical and boring purchase(commodities), marketing to humans must rise towards “cognitive luxury”. If functionality is a commodity, the only sustainable competitive advantage is deep emotional connection, now supported by Neuro-IA and Spatial Computing.
- The Tangible Internet: With devices like the Vision Pro or Quest 3, we move from flat screens to immersive experiences. Brands will have to create digital Twins (USDZ/GLB files) of their products so that we can virtually “touch” them before buying.
- Neuromarketing democratized: AI allows us to predict where a user will look with 90% accuracy before launching a campaign, or to analyze facial micro-expressions to detect emotions in real time. Design is no longer intuitive but predictive.
Conclusion: Whispering to the algorithm, touching the heart
The future of marketing does not belong to whoever shouts the loudest. It belongs to whoever is able to whisper with mathematical precision into the ears of algorithms (B2A, GEO, MCP) and, at the same time, touch with neurological depth the heart of people (immersive experiences, brand, values).
Don’t try to use human persuasion tools with an AI agent, nor bore a human with raw data. Design separate but integrated strategies.
The tsunami of technology deflation is coming for all brands that don’t provide real value. The question is: Are you building a brand that a human wants and that an agent can understand, or are you still relying on the usual “cheap excuses”?
Do you need to reorient your digital strategy in the face of this new paradigm?
At Noergia we don’t have a crystal ball, but we do understand the data and technology that is shaping the market. We can help you prepare your data infrastructure, optimize your presence for AI and design strategies that will survive 2030.
References:
https://unorthodox-economics.com/en/temas/technological-deflation/
